Project Activities
This project used multiple data sources and methods of analysis to describe the management skills, leadership orientations, and executive behaviors of school leaders and to estimate the relationships of these attributes with school, teacher, and student outcomes. The data included district and state administrative data on students, teachers, administrators, and schools, as well as surveys of teachers, assistant principals, and principals, observational time-use data on principals, and interviews with school and district leadership. The study used multiple methods and relies on longitudinal data analysis techniques including fixed-effects analyses to describe the workforce of school leaders and to estimate the relationship between school-leader characteristics and school outcomes (including teacher turnover, school climate, and student achievement).
Structured Abstract
Setting
This study took place in three large urban school districts in Texas, Kentucky, and Wisconsin.
Sample
The population of this study included principals, assistant principals, teachers, district staff, and students in the three participating districts. The analyses based solely on administrative data included the full population of teachers, assistant principals, and principals in the participating school districts. The principal observations and interviews were done with a stratified random sample in each district giving greater weight to principals in high schools and schools serving students at risk of school failure based on poverty and other student background characteristics.
Research design and methods
The project collected, linked, and analyzed five types of data: (1) observational time-use data for principals gathered via shadowing; (2) survey responses of principals, assistant principals, teachers, and other district employees; (3) formal multi-rater assessments of management skills and leadership capacities completed by principals, assistant principals, and a sample of teachers; (4) interviews with school and district leaders; and (5) administrative data, including student test score results and human resource information. The analysis modeled student, teacher and school outcomes as a function of school leadership using regression-based longitudinal-data techniques that control for other factors affecting these outcomes. Interviews with school and district leaders and observations in schools complimented the statistical analyses.
Control condition
There was no control condition.
Key measures
The constructs of interest were school leader management attributes, skills, leadership orientations, and executive behaviors. The key outcomes were student achievement gains, students' commitment to learning, parents' satisfaction with the school's performance, and teachers' satisfaction, commitment and career choices. The measures for these were built on measures employed by the same research team in a 2008 mixed-methods study of school leaders in Miami-Dade County Public Schools including the observation time-use protocol; the survey filled out by leaders and teachers; a task effectiveness inventory used to rate school leaders also filled out by leaders and teachers; the Multifactor Leadership Questionnaire to measure leadership orientation filled out by leaders and teachers; and protocols for interviewing principals and district leaders. In addition, administrative data collected includes: (1) student performance on standardized tests in the core subjects, both at the student and school levels; (2) student demographic data; (3) teacher data on yearly job placement, demographics, certification status, experience, and salary; (4) school leader data on demographics, total experience within and outside the district, and degrees and credentials earned; and (5) aggregated responses to school climate surveys by students, parents, and staff administered by the districts.
Data analytic strategy
The analysis included descriptive analysis, more advanced multivariate methods, and qualitative analysis. For example, management skills of school leaders were measured using factor-analyzed responses to the task effectiveness inventory. Cross-sectional multivariate analyses, structural equation modeling, and hierarchical modeling were used to estimate the relationship between independent variables (management skills, leadership orientations, and executive behaviors) and various school, teacher, and student outcomes. Interviews were used to assess the degree to which district and school administrators indicate that management skills and leadership are considerations for principal and assistant principal assignments, especially in the assignments of leaders to the lowest performing schools.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Publications:
Journal article, monograph, or newsletter
Beteille, T., Kalogrides, D., and Loeb, S. (2012). Effective Schools: Teacher Hiring, Assignment, Development, and Retention. Education Finance and Policy, 7(3): 269-304.
Beteille, T., Kalogrides, D., and Loeb, S. (2012). Stepping Stones: Principal Career Paths and School Outcomes. Social Science Research, 41(4): 904-919.
Grissom, J. A., Kalogrides, D., and Loeb, S. (2015). Using Student Test Scores to Measure Principal Performance. Education Evaluation and Policy Analysis, 37(1): 3-28.
Grissom, J. A., Loeb, S., & Master, B. (2013). Effective Instructional Time Use for School Leaders: Longitudinal Evidence from Observations of Principals. Educational Researcher, 42(8): 433-444.
Grissom, J. A., Loeb, S., and Mitani, H. (2015). Principal Time Management Skills: Explaining Patterns in Principals' Time Use, Job Stress, and Perceived Effectiveness. Journal of Educational Administration , 53(6): 773-793.
Grissom, J. A., Loeb, S., and Nakashima, N.A. (2014). Strategic Involuntary Teacher Transfers and Teacher Performance: Examining Equity and Efficiency. Journal of Policy Analysis and Management, 33(1): 112-140.
Grissom, J.A. and Loeb, S. (2017). Assessing Principals' Assessments: Subjective Evaluations of Teacher Effectiveness in Low- and High Stakes-Environments. Education Finance and Policy, 12(3): 369-395.
Grissom, J.A., and Loeb, S. (2011). Triangulating Principal Effectiveness How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills. American Educational Research Journal, 48(5): 1091-1123.
Kalogrides, D., and Loeb, S. (2013). Different Teachers, Different Peers: The Magnitude of Student Sorting Within Schools. Educational Researcher, 42(6): 304-316.
Kalogrides, D., Loeb, S., and Beteille, T. (2013). Systematic Sorting: Teacher Characteristics and Class Assignments. Sociology of Education, 86(2): 103-123.
Loeb, S. Kasman, M., and Valant, J. (2013). Principals' Perceptions of Competition for Students in Milwaukee Schools. Education Finance and Policy, 8(1): 43-73.
Loeb, S., Beteille, T., and Kalogrides, D. (2012). Effective Schools: Teacher Hiring, Assignment, Development, and Retention. Education Finance and Policy, 7(3): 269-304.
Myung, J., Loeb, S., and Horng, E. (2011). Tapping the Principal Pipeline: Identifying Talent for Future School Leadership in the Absence of Formal Succession Management Programs. Education Administration Quarterly, 47(5): 695-727.
Ronfeldt, F., Farmer, S., McQueen, K., and Grissom, J.A. (2015). Teacher Collaboration in Instructional Teams and Students Achievement. American Educational Research Journal , 52(3): 475-514.
Sun, M., Loeb, S. and Grissom, J. (2017). Building Teacher Teams: Positive Spillovers from More Effective Colleagues. Educational Evaluation and Policy Analysis, 39(1): 104-125.
Nongovernment report, issue brief, or practice guide
Loeb, S. & Grissom, J. (2013). What Do We Know about the Use of Value-Added Measures for Principal Evaluation? What We Know Series: Value-Added Methods and Applications. The Carnegie Foundation.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
